https://github.com/montara-io/dbt-command-center

Never sift through endless dbt™ logs again. dbt Command Center is a free, open-source, local web application that provides a user-friendly interface to monitor and manage dbt runs.
https://github.com/montara-io/dbt-command-center

analytics-engineering bigquery data-analysis data-catalog data-engineering data-lineage data-observability data-pipeline data-pipelines data-validation data-warehouse dataops dbt dbt-packages elt etl orchestration python redshift

Last synced: about 2 months ago
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Never sift through endless dbt™ logs again. dbt Command Center is a free, open-source, local web application that provides a user-friendly interface to monitor and manage dbt runs.

• Host: GitHub
• URL: https://github.com/montara-io/dbt-command-center
• Owner: montara-io
• License: mit
• Created: 2024-05-13T05:27:44.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2025-04-20T20:12:37.000Z (2 months ago)
• Last Synced: 2025-04-20T21:24:35.153Z (2 months ago)
• Topics: analytics-engineering, bigquery, data-analysis, data-catalog, data-engineering, data-lineage, data-observability, data-pipeline, data-pipelines, data-validation, data-warehouse, dataops, dbt, dbt-packages, elt, etl, orchestration, python, redshift
• Language: TypeScript
• Homepage: https://montara.io
• Size: 3.55 MB
• Stars: 28
• Watchers: 3
• Forks: 0
• Open Issues: 9
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

• awesome-dbt - dbt-command-center - A local web application that provides a user-friendly interface to monitor and manage dbt runs. (Utilities)

README

        
# 🚀 dbt™ Command Center

Never drill through endless dbt™ logs again. dbt™ Command Center is a local web application that provides a user-friendly interface to monitor and manage dbt™ runs.



  

    
Watch a 2-min demo video

  

  

    

  



## Getting started

- Install the package with `pip install dbt-command-center`

- Run `dcc` instead of `dbt` to start the dbt™ Command Center. You can pass the same arguments as you would to `dbt run`. For example `dcc run --models my_model --full-refresh`.

## Contributing

- Clone the repository with `git clone`

- If you changed your web application run `npm run build` to update the build folder.

- Run `cd web && npm run build && cd .. && rm -rf dist && python setup.py sdist bdist_wheel` to create source and binary distribution files in the dist/ directory.

- (Optional) Test your package locally by installing it with `pip install --force-reinstall --no-deps /dbt-command-center/dist/dbt_command_center-.tar.gz`

## Release a new version to PyPI

- Don't forget to update the version in `setup.py`

- A new version is automatically released with every push to the main branch. The GitHub Action will build the package and upload it to PyPI.

### Anonymous usage data

We strive to make dbt™ Command Center better by understanding how it is used. To do this, we collect anonymous usage data. This does not include any personal information or data from your dbt™ runs. You can opt-out by setting the environment variable `DCC_DISABLE_ANALYTICS` to `true`.